From merging galaxies to quasars: The evolution of nuclear activity in luminous and ultraluminous infrared galaxies

We present the largest X-ray survey (∼80 objects) of luminous and ultraluminous infrared galaxies (U/LIRGs) to date. The large infrared luminosities in these objects are thought to arise from either star formation triggered by the merging of disk galaxies or by nuclear activity. U/LIRGs have been purported to be the progenitors of some quasars. In this thesis, we utilize data from Chandra, XMM-Newton, and Suzaku X-ray observatories to quantify the contribution to the overall power of U/LIRGs by starbursts or active galactic nuclei (AGNs). A goal of this project is to statistically examine how the starburst-to-AGN ratio evolves as a function of merger stage. We find that a majority of U/LIRGs are X-ray faint. This may be a result of high obscuration or weak nuclear activity. The dearth of detected counts makes traditional fitting difficult. As a solution, we developed a method of using hardness ratios (HR) to estimate the spectral shapes of these weak sources. Both observational evidence and simulations show that this method is effective for sources with intrinsic column densities below ∼10 22 cm-2 and applicable to sources with only tens of detected counts. Applying the HR method and traditional spectral fitting to the U/LIRG data and that of 26 PG quasars, we find a correlation of AGN dominance with dust temperature, optical spectral type, and merger stage. The probability of having a powerful AGN increases along the merger sequence. However, the AGNs can turn on at any time, as evidenced by a large number of AGNs detected in binary U/LIRGs. Starburst dominates the total power in U/LIRGs prior to the merger. Then the black hole grows rapidly during coalescence. At this time, the AGN is likely to begin driving galactic scale winds which will quench star formation, resulting in a luminous quasar. These conclusions are in general agreement with results obtained at other wavelengths and current theoretical models.